SOIL
SOIL
SOIL
Articles | Volume 11, issue 2
Articles | Volume 11, issue 2
https://doi.org/10.5194/soil-11-655-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/soil-11-655-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 2
Original research article
 | 
25 Sep 2025
Original research article |  | 25 Sep 2025

Combining electromagnetic induction and satellite-based NDVI data for improved determination of management zones for sustainable crop production

Salar Saeed Dogar, Cosimo Brogi, Dave O'Leary, Ixchel M. Hernández-Ochoa, Marco Donat, Harry Vereecken, and Johan Alexander Huisman

Viewed

Total article views: 1,677 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,385 252 40 1,677 46 67
  • HTML: 1,385
  • PDF: 252
  • XML: 40
  • Total: 1,677
  • BibTeX: 46
  • EndNote: 67
Views and downloads (calculated since 28 Feb 2025)
Cumulative views and downloads (calculated since 28 Feb 2025)

Viewed (geographical distribution)

Total article views: 1,677 (including HTML, PDF, and XML) Thereof 1,677 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 25 Nov 2025
Download
Short summary
Farmers need precise information about their fields to use water, fertilizers, and other resources efficiently. This study combines underground soil data and satellite images to create detailed field maps using advanced machine learning. By testing different ways of processing data, we ensured a balanced and accurate approach. The results help farmers manage their land more effectively, leading to better harvests and more sustainable farming practices.
Read more
Share
Special issue
Agrogeophysics: illuminating soil's hidden dimensions